Methodology

How AIOStory measures, and what it refuses to make up

AIOStory reads the locations you enter from public on-page signals, scores each on six pillars with the AIOInsights engine, and synthesizes a six-chapter story where every sentence traces to a measured value. No LLM in the scoring or synthesis. No randomness. The same inputs always produce the same story, word for word.

The measurement

Six pillars, scored per location

AIOStory does not build its own scorer. It reuses the AIOInsights single site engine, calling it once per location. Each pillar is scored 0 to 10 and shown as 0 to 100. A signal is strong at 70 and above, weak below 50.

Clarity

Can AI tell what you do.

Identity

Does AI know who you are.

Substance

Is there enough to quote.

Reach

Can AI read the page at all.

Trust

Can AI see proof you are trusted.

Locality

Can AI place you on the map.

The synthesis

Six chapters, every line traced to data

The per-location scores feed a fixed synthesis that produces six story chapters. Which pillars feed which chapter is not improvised at runtime. The mapping is defined in a fixed file, pillars-to-chapters.json, so chapter feeding is deterministic and auditable.

The six chapters

Who AI Thinks Your Brand Is reports the dominant brand name AI reads and how confidently it can describe the brand, from Clarity, Identity, and Substance averaged across readable locations.

What AI Gets Wrong surfaces on-page inconsistencies: more than one brand name across locations, or wide swings in how clearly each location states who it is. This is on-page consistency only. Factual freshness of hours, addresses, and offers is checked per location in a full audit, not here.

Where AI Looks Elsewhere lists locations AI cannot read at all, blocked or unreachable, or barely reads with low Reach. When AI cannot read a location, it recommends one it can.

Missing Chapters flags any pillar that scores weak at most readable locations. That is treated as a brand-level gap, not a one-location fix.

Trust Signals reports which locations expose machine-readable proof, ratings in structured data, linked review profiles, local-business signals, and which do not.

The Fuller Story states honestly how many locations were sampled, N of M, and what a full per-location, per-microsite audit adds.

If a chapter has no data behind it, the report says "Not enough sampled locations to assess" rather than inventing filler.

The sampling rule

SAMPLE_CAP = 8, and N of M is always disclosed

You can enter 2 to 25 location URLs, one per line. We dedupe by host first, so the same site entered twice counts once. The free read then samples the first eight, SAMPLE_CAP = 8, and the report always discloses the coverage as "N of M sampled" so you know how much of your brand was read.

A full audit, the paid step, evaluates every location and microsite individually. It is the only path that reads beyond the sample and beyond homepage-level signals.

Readability detection

When AI cannot read a website

Some locations are invisible to AI. AIOStory detects this directly. A location is marked unreadable when it is blocked by a bot challenge, or when it is unreachable. Those locations are not scored on the six pillars as if everything were fine. They appear in the "Where AI Looks Elsewhere" chapter, because when AI cannot read one location it will recommend a location it can.

The guarantees

Deterministic, and nothing invented

There is no LLM in the scoring or the synthesis. There is no randomness. There is no paid API call to a chatbot. The pillar scores come from the AIOInsights engine, and the chapter mapping is the fixed pillars-to-chapters.json file. As a result, the same inputs yield the same story word for word.

We never claim anything we do not measure. Every chapter sentence traces back to a value we read. When the data is not there, we say so instead of filling the gap.

Scope limits

What the free read does not do

We read homepage-level public signals per location. We do not crawl every page of every site in the free read.

Factual freshness, whether hours, addresses, and offers are current and consistent, and per-microsite depth are full-audit work only. The free read does not verify them.

Reviews are read from on-site machine-readable signals, structured data and linked profiles exposed on the location's own site. Reviews living only on Google or Yelp do not count unless they are exposed on the site where AI can read them. We do not query live Google or Yelp.

Your move

See the story AI is telling your customers

It takes your location URLs and about two minutes. The story might surprise you.

Reveal my brand story